The lack of comprehensive data on the bulk density of soil types at the European scale is a serious limitation for pan-European environmental risk assessment studies. Although many predictive methods have been published, most have limitations for application across Europe. We therefore developed a semi-empirical method of prediction using a large UK dataset and tested it and some other methods against a pan-European dataset. Our method indicated that five separate conceptual groupings of the development dataset were valid. Predictive equations based on multiple regression analysis for each of the five groups explained between 40 and 69% of the measured variation in each one. When used to predict measured bulk density from the European dataset, the equations explained 63% of the measured variation in mineral horizons from soil environments similar to those of the development dataset with a predictive mean percentage error of ±11%. The equation for organic horizons explained 29% of the measured variation in bulk density with a mean percentage error of ±39%. For those horizons from soil environments outside those of the development dataset, prediction of bulk density was relatively poor, even when using soil region-specific PTFs derived from its data. It was concluded that, for these soils, factors other than organic carbon, particle size, horizon depth, mechanical cultivation or parent material have a major influence on bulk density and need further investigation.

We review the nature and importance of soil factors implicated in the formation of secondary ferrimagnetic minerals in soils and palaeosols worldwide. The findings are examined with respect to temperate regions through a comprehensive analysis of over 5000 samples of surface soil from England and Wales taken from a 5 x 5 km grid. Over 30 soil and environmental attributes are considered for each sample as proxies for soil forming factors. Measurements of low field magnetic susceptibility (mass specific) and frequency-dependent susceptibility (mass specific and percentage) on each sample provide estimates of the concentration and grain size of ferrimagnetic minerals. Maps of soil magnetism across England and Wales show non-random distributions and clusters. One sub-set of data is clearly linked to contamination from atmospheric pollution, and excluded from subsequent analyses. The concentration of ferrimagnetic minerals in the non-polluted set is broadly proportional to the concentration of minerals falling into the viscous superparamagnetic domain size range (~ 15 -25 nm). This set shows clusters of high magnetic concentrations particularly over specific parent materials such as schists and slates, mudstones and limestones. Bivariate analyses and linear multiple regression models show that the main controlling factors are parent material and drainage, the latter represented by soil drainage classes and particle-size. Together these two factors account for ~ 30 % of the magnetic variability in the complete dataset. A second group of factors, including climate (mean annual rainfall), relief (slope and altitude), and organisms (land use, organic carbon and pH) have subordinate control. Climate as represented by mean annual temperature and pedogenic time is deemed not relevant at these spatio-temporal scales.

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S U M M A R YA new method is presented for fast quantification of urban pollution sources in atmospheric particulate matter (PM). The remanent magnetization of PM samples collected in Switzerland at sites with different exposures to pollution sources is analysed. The coercivity distribution of each sample is calculated from detailed demagnetization curves of anhysteretic remanent magnetization (ARM) and is modelled using a linear combination of appropriate functions which represent the contribution of different sources of magnetic minerals to the total magnetization. Two magnetic components, C1 and C2, are identified in all samples. The low-coercivity component C1 predominates in less polluted sites, whereas the concentration of the highercoercivity component C2 is large in urban areas. The same sites were monitored independently by Hüglin using detailed chemical analysis and a quantitative source attribution of the PM. His results are compared with the magnetic component analysis. The absolute and relative magnetic contributions of component C2 correlate very well with absolute and relative mass contributions of exhaust emissions, respectively. Traffic is the most important PM pollution source in Switzerland: it includes exhaust emissions and abrasion products released by vehicle brakes. Component C2 and traffic-related PM sources correlate well, which is encouraging for the implementation of non-destructive magnetic methods as an economic alternative to chemical analysis when mapping urban dust pollution.